Jenniferplusplus16h ago

There's one very important thing I would like everyone to try to remember this week, and it is that AI companies are full of shit

Only rarely do their claims actually bear scrutiny, and those are only the mildest of claims they make.

So, anthropic is claiming that their new, secret, unreleased model is hyper competent at finding computer security vulnerabilities and they're *too scared* to release it into the wild.

Except all the AI companies have been making the same hypercompetence claims about literally every avenue of knowledge work for 3+ years, and it's literally never true. So please keep in mind the highly likely possibility that this is mostly or entirely bullshit marketing meant to distract you from the absolute garbage fire that is the code base of the poster child application for "agentically" developed software

You may now resume doom scrolling. Thank you

Show threadBogdan Buduroiu12h ago

@jenniferplusplus I seriously doubt this is smoke and mirrors, recent models have improved significantly for cybersec and the industry is noticing:

https://mastodon.social/@bagder/116336957584445742

https://www.theregister.com/2026/03/26/greg_kroahhartman_ai_kernel/

The industry consensus seems to be that there's going to be a torrent of vulnerabilities being found in all sorts of software, and they're not prepared to handle the blast radius. It's not surprising that Anthropic wants to give a select few a head start to tackle them. It would be nice if their token fund was open to all OSS projects to apply.

I'm also pressing "X doubt" that you spend months coordinating between AWS, Apple, Microsoft, Google, and the Linux Foundation to organise this just because your tool's code leaked online.

AI bug reports went from junk to legit overnight, says Linux kernel czar

Interview: Greg Kroah-Hartman can't explain the inflection point, but it's not slowing down or going away

The Register
Show threadKraftwerk-Das Model Collapse11h ago
@budududuroiu @jenniferplusplus some people have published numbers or noticed "a significant increase in quality" but none of these things bear any scientific rigor. My guess is that the one huge trick anthropic pulled was merely a bigger context window. Sure, that tends to give more context-related (not "true" or "accurate") results (duh!) but it's hardly revolutionary. LLMs are still statistical models doing fancy autocomplete & they know nothing about the world, I'll hold my breath
Show threadAndrocat

@dngrs @budududuroiu @jenniferplusplus

People keep getting tricked by framing.
LLM companies frame what the models are doing as something else than what it is (autocomplete), and people whose competence is not in epistemic evaluation then look at the results based on the framing, rather than "this is autocomplete, it has to answer something, so it makes something up".

And then other people take those soundbites and run with them.
"Did you hear? Mr. Big Name said this stuff really works!"

7:01amWeb